Develop High-Performance GPU Kernels in C++ with NVIDIA CUDA Tile | NVIDIA Technical Blog

This post introduces CUDA Tile C++, an extension of the CUDA Tile programming model to C++. It allows developers to write tile kernels in C++ using multi-dimensional tensor spans and partition views, abstracting low-level GPU parallelism, memory movement, and hardware features. The post provides examples of vector addition and discusses optimizations like __restrict__ pointer qualifiers and 16-byte alignment, as well as profiling with Nsight Compute. It requires GPUs with compute capability 8.x or newer, NVIDIA Driver R580+, and CUDA Toolkit 13.3+.